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<!DOCTYPE html>
<html>
<head>
<title>Course introduction</title>
<meta charset="utf-8">
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<textarea id="source">
class: center, middle
# Better analysis with python
*Liam Brannigan (with help from Lucy Tallents)*
MISU, December 2017
---
# Key concepts
- Much easier to write good code with **labelled** data
- Analysing in **parallel** need not be complicated
- **Just in time** compilation may save you a lot of time
---
# Things we *will* do today
- See how these concepts work in practice
- Look at some realistic examples
# Things we will *not* do today
- Go into much detail
---
# Objectives
You will:
- be able to take advantage of major recent advances in analysis software
- have a set of materials that you can use for practice to get yourself going
You will not be able to:
- use these packages like an expert
**Focus on the key concepts, not the details of the code**.
---
# Plan
1. Pandas and labelled data
2. Going parallel with dask
3. Labels and parallel for netcdf files with xarray
4. Compiling with numba
</textarea>
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